[CVPR2024 Highlight]GLEE: General Object Foundation Model for Images and Videos at Scale
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Updated
May 8, 2024 - Python
[CVPR2024 Highlight]GLEE: General Object Foundation Model for Images and Videos at Scale
API for Grounding DINO 1.5: IDEA Research's Most Capable Open-World Object Detection Model Series
Creating multimodal multitask models
Image Instance Segmentation - Zero Shot - OpenAI's CLIP + Meta's SAM
Official code for our paper "Enhancing Novel Object Detection via Cooperative Foundational Models"
A curated list of papers, datasets and resources pertaining to zero-shot object detection.
Resolving semantic confusions for improved zero-shot detection (BMVC 2022)
Use Grounding DINO, Segment Anything, and CLIP to label objects in images.
使用onnxruntime部署GroundingDINO开放世界目标检测,包含C++和Python两个版本的程序
[CVPR2024] Official repository of the paper "The devil is in the fine-grained details: Evaluating open-vocabulary object detectors for fine-grained understanding."
EfficientSAM + YOLO World base model for use with Autodistill.
YOLO World base module for use with Autodistill.
OWLv2 base model for use with Autodistill.
Use PaliGemma to auto-label data for use in training fine-tuned vision models.
Generate an image collage with computer vision.
This project represents a GroundingDINO Inference (zero-shot object detection) procedure with both methods (CLI and Script). This implementation will help the reader to know the sequence of commands and exemplifying commands for running a quick zero-shot object detection. Additionally, the reader may get insight into code (script) execution.
CoDet base model for use with Autodistill.
CLIP based Zero Shot Instance Segmentation
Qwen-VL base model for use with Autodistill.
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